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Adrian Ally

Researcher at BC Cancer Agency

Publications -  33
Citations -  28748

Adrian Ally is an academic researcher from BC Cancer Agency. The author has contributed to research in topics: DNA methylation & Gene. The author has an hindex of 29, co-authored 33 publications receiving 20997 citations. Previous affiliations of Adrian Ally include University of Texas MD Anderson Cancer Center & National Institutes of Health.

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Journal Article

The Cancer Genome Atlas Pan-Cancer analysis project

Kyle Chang, +337 more
- 01 Sep 2013 - 
TL;DR: The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels as mentioned in this paper.
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Comprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas.

Daniel J. Brat, +306 more
TL;DR: The integration of genomewide data from multiple platforms delineated three molecular classes of lower-grade gliomas that were more concordant with IDH, 1p/19q, and TP53 status than with histologic class.
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Genomic Classification of Cutaneous Melanoma

Rehan Akbani, +351 more
- 18 Jun 2015 - 
TL;DR: This clinicopathological and multi-dimensional analysis suggests that the prognosis of melanoma patients with regional metastases is influenced by tumor stroma immunobiology, offering insights to further personalize therapeutic decision-making.
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The Molecular Taxonomy of Primary Prostate Cancer

Adam Abeshouse, +311 more
- 05 Nov 2015 - 
TL;DR: The Cancer Genome Atlas (TCGA) has been used for a comprehensive molecular analysis of primary prostate carcinomas as discussed by the authors, revealing substantial heterogeneity among primary prostate cancers, evident in the spectrum of molecular abnormalities and its variable clinical course.
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Integrated Genomic Characterization of Papillary Thyroid Carcinoma

Nishant Agrawal, +242 more
- 23 Oct 2014 - 
TL;DR: The genomic landscape of 496 PTCs is described and a reclassification of thyroid cancers into molecular subtypes that better reflect their underlying signaling and differentiation properties is proposed, which has the potential to improve their pathological classification and better inform the management of the disease.